Identification Error Probability Research Articles

Reliability and Accessibility of Low-Latency V2I Channel Training Protocol Using Cover-Free Coding: Win–Win or Tradeoff ?

Future vehicle-to-infrastructure communications in a multi-vehicle environment highly depend on the acquisition of wireless orthogonal frequency division multiplexed (OFDM) channels through the conventional pilot-tone based channel training protocol. However, this protocol can be easily compromised by a pilot-aware attacker spoofing/jamming/nulling those pilot tones, which have been designated for multiple vehicles. To solve this issue, we propose merging the multi-vehicle signal characteristic into the well-known cover-free coding technique for securely and retrievably coding pilot tones of multiple vehicles. In particular, multiple vehicles encode and convey their own pilot tones into diversified subcarrier activation patterns (SAPs). Then, road side unit observes the superposition of those encoded SAPs and re-designs the decoding procedure using signal independence characteristic such that those SAPs, though camouflaged by malicious signals in wireless environment, could be separated, identified, and decoded into original pilots. The protocol reliability is formulated using pilot identification error probability (IEP), and the protocol $\xi$ -accessibility is defined by the ratio of the number of accessible vehicles to the consumed OFDM symbols under the constraint of IEP less than $\xi$ . We prove that a win–win relationship between reliability and accessibility always exists and also demonstrate how more number of antennas of the attacker could improve the reliability better. Finally, numerical results verify how the proposed method is enabled to support ultra-reliable ( $1-\xi \geq 99.999\%$ ) and ultra-low-latency (up to 1.5 ms) multi-vehicle access for channel training under an Long Term Evolution (LTE) 20 MHz bandwidth.

Hierarchical 2-D Feature Coding for Secure Pilot Authentication in Multi-User Multi-Antenna OFDM Systems: A Reliability Bound Contraction Perspective

Due to the publicly known and deterministic characteristic of pilot tones, pilot authentication (PA) in multi-user multi-antenna orthogonal frequency-division multiplexing systems is very susceptible to the jamming/nulling/spoofing behaviors. To solve this, in this paper, we develop a hierarchical 2-D feature (H2DF) coding theory that exploits the hidden pilot signal features, i.e., the energy feature and independence feature, to secure pilot information coding which is applied between legitimate parties through a well-designed five-layer hierarchical coding model to achieve secure multiuser PA (SMPA). The reliability of SMPA is characterized using the identification error probability (IEP) of pilot encoding and decoding with the exact closed-form upper and lower bounds. However, this phenomenon of non-tight bounds brings about the risk of long-term instability in SMPA. Therefore, a reliability bound contraction theory is developed to shrink the bound interval, and practically, this is done by an easy-to-implement technique, namely, codebook partition within the H2DF code. In this process, a tradeoff between the upper and lower bounds of IEP is identified and a problem of optimal upper and lower bound tradeoff is formulated, with the objective of optimizing the cardinality of sub-codebooks such that the upper and lower bounds coincide. Solving this, we finally derive an exact closed-form expression for IEP, which realizes a stable and highly reliable SMPA. Numerical results validate the stability and resilience of H2DF coding in SMPA.

Integrated Identification and Quantification Error Probabilities for Shotgun Proteomics

Protein quantification by label-free shotgun proteomics experiments is plagued by a multitude of error sources. Typical pipelines for identifying differential proteins use intermediate filters to control the error rate. However, they often ignore certain error sources and, moreover, regard filtered lists as completely correct in subsequent steps. These two indiscretions can easily lead to a loss of control of the false discovery rate (FDR). We propose a probabilistic graphical model, Triqler, that propagates error information through all steps, employing distributions in favor of point estimates, most notably for missing value imputation. The model outputs posterior probabilities for fold changes between treatment groups, highlighting uncertainty rather than hiding it. We analyzed 3 engineered data sets and achieved FDR control and high sensitivity, even for truly absent proteins. In a bladder cancer clinical data set we discovered 35 proteins at 5% FDR, whereas the original study discovered 1 and MaxQuant/Perseus 4 proteins at this threshold. Compellingly, these 35 proteins showed enrichment for functional annotation terms, whereas the top ranked proteins reported by MaxQuant/Perseus showed no enrichment. The model executes in minutes and is freely available at https://pypi.org/project/triqler/.

PHY-Layer Cover-Free Coding for Wireless Pilot Authentication in IoV Communications: Protocol Design and Ultra-Security Proof

Wireless channel state information (CSI) from intelligent vehicles to the roadside unit (RSU) is a must for vehicleto-infrastructure (V2I) communications in Internet of Vehicles, but easily suffers the risks of being attacked due to the publicly known and deterministic characteristic of PHY-layer pilots that are employed for CSI acquisition. This incurs the issue of wireless pilot authentication (WPA), that is, verifying the authenticity of pilots and claimed CSIs. In this paper, we, for multiantenna V2I orthogonal frequency division multiplexed communications, develop a PHY-layer cover-free (PHY-CF) coding theory to build up a secure WPA (SWPA) protocol. Here, we encode and convey vehicle pilot signals into diversified subcarrier activation patterns (SAPs) on the time-frequency domain by employing cover-free coding. We redesign the decoding procedure using the signal independence characteristic such that those encoded SAPs, though camouflaged by malicious signals and superimposed onto each other in wireless environment, could be separated, identified and decoded into the original pilots securely. For this protocol, we prove that perfect pilot conveying and separation could be both guaranteed. We formulate the pilot identification error probability (IEP) and show how PHY-CF coding could help position the location of attacker and reduce IEP to further achieve ultrasecurity. Considering 20 MHz long-term evolution bandwidth, we prove that the number of co-time co-frequency vehicles that are securely authenticated achieves up to 19 × X for X serving sectors of base station type RSU and the latency time of uplink data access is up to 1.5 ms, thus furthering the autonomous driving. Computer simulations comprehensively verify those benefits of proposed SWPA protocol.

Identification potential of online handwritten signature verification

This paper presents a comparison of natural and artificial intelligences in identifying operators of information-processing systems and their functional state based on handwriting. The cause of the large scatter in the person identification error probability is determined. It is concluded that at the present level of knowledge, the best result achieved in solving the problem by artificial intelligence systems is close to that potentially possible. It is substantiated that online handwritten signature verification is suitable for identifying the functional state of operators of human-machine systems in professional activities.

Application of Two-Level Joint Information Fusion Model in Intelligent Vehicle

This paper proposes a two-level joint information fusion model combining BP neural network and D-S evidence theory. The model of great practical value reduces target identification error probability by multiple features of the target information, shows good scalability with its two steps of information fusion model, and conveniently increases/reduces feature fusion information source according to different situations and different objects. The method used for intelligent vehicles has good flexibility and robustness in tracking and avoiding obstacle. The simulation and real vehicle tests have verified effectiveness of the method.

Parallel systems under two sequential attacks with imperfect detection of the first attack outcome

The paper compares the efficiency of single and double attack against a system consisting of identical parallel elements. An attacker maximizes the system vulnerability (probability of total destruction). In order to destroy the system, the attacker distributes its constrained resource optimally across two attacks and chooses the number of elements to be attacked in the first attack. The attacker observes which elements are destroyed and not destroyed in the first attack and allocates its remaining resource into attacking the remaining elements in the second attack. The paper considers two types of identification errors: wrong identification of a destroyed element as not destroyed, and wrong identification of a not destroyed element as destroyed. First, the influence of the identification error probabilities on the optimal attack strategy against a system with a fixed number of elements is analysed. Thereafter, a minmax two-period game between the attacker and the defender is considered, in which the defender in the first period distributes its constrained resource between deploying redundant elements and protecting them against the attack in the second period. It is shown how the identification error probabilities affect the defence strategy.

Threshold-based identification of wireless SAW RFID-tags with pulse position encoding

In recent decades, there have been designed and developed passive surface acoustic wave radio frequency identification tags with time position encoding in groups of slots. For such tags identified when the received pulse-burst exceeds a threshold, we specify the generic identification (ID) error probability and optimize the threshold employing the Marcum Q-function of first order. As examples, we estimate the ID errors for the one-group 28-slot tag and Barker encoding. It is shown that, under the ideal conditions of equal SNRs (14.8 dB) in On-pulses and zeroth in Off-pulses, the ID error probability lesser 1% (one slip per 100 readings) can be guarantied with single reading for any reasonable number of slots. It becomes lesser 0.1% (1 slip per 1000 readings) with seven or lesser slots.

Isomer identification of chlorinated dibenzo-p-dioxins by orthogonal spectroscopic and chromatographic techniques

Isomer differentiation of chlorinated dibenzo-p-dioxin (CDD) isomer pair components was examined by three orthogonal chromatographic (gas chromatography, liquid chromatography, and micellar electrokinetic chromatography) techniques and three orthogonal spectroscopic (Fourier transform infrared and carbon-13 and proton nuclear magnetic resonance) techniques. Synthetic CDD isomer pair mixtures from the same sample set were separated by methods using independent partitioning dynamics and identified by spectroscopic methods using independent energy/structure transformations. This integrated approach using orthogonal methods minimizes isomer identification error probability and results in an excellent agreement among methods in isomer assignment.

Scene identification error probabilities for evaluating Earth radiation measurements

The computation of radiant fluxes from radiance measurements by satellite radiometers requires the use of a bidirectional model. The bidirectional model, in turn, depends on the scene, so that a scene identification algorithm is required. The accuracy of scene identification varies with viewing zenith angle due mainly to geometric effects of the clouds and the measurements. This paper investigates the effects of viewing zenith angle on scene identification errors. Along‐track measurements from the Earth Radiation Budget Experiment (ERBE) have been analyzed to quantify the probabilities of identifying a given scene as to its level of cloudiness, as used by the ERBE data processing system. Scene identification probabilities were initially computed on the basis of a select set of pixels. These restricted scene identification probabilities were then used to compute scene identification probabilities for all pixels, including those of marginal scene type. These probabilities are found to be functions of viewing zenith angle, but are insensitive to other parameters such as solar zenith angle, relative azimuth, and latitude, except in the Sun glint region. For most cases, the scene identification probabilities change very slowly for viewing zenith angle less than 40°, but change rapidly for viewing zenith angle greater than 50°. With increasing viewing zenith angles, the probability increases for identifying, a scene as being more cloudy than its true cloud class. These results are useful for evaluation of flux errors due to scene identification errors in the data processing.